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Aaron Levie 分享了关于Agent 实践的观察：There’s still so much opportunity in the diffusion of AI into the real world. Most enterprises are going to need a ton of support to be able to apply the model breakthroughs to their workflows. Intelligence alone is not...
Amjad Masad 分享了关于模型研究的观察：Interesting drop from former Anthropic employee: Hackers prefer to use massively subsidized labs AI subscriptions for attacks as opposed to open models.
Plus: Russian hackers are trying to steal US nuclear scientists’ emails, the State Department bans known scammers from entering the United States, and more.
You’re an action hero, and you need a camera to match. We guide you through all the models, plus accessory recommendations and hidden software tricks to try.
Anthropic released Claude Opus 5 on Friday, a model the company says delivers nearly all the intelligence of its top-of-the-line Claude Fable 5 at half the cost — a launch that signals how the AI race is shifting from raw capability to the economics of daily use. The model, available immediately on all of Anthropic's platforms, is priced at $5 per million input tokens and $25 per million output tokens, unchanged from its predecessor, Opus 4.8 . It becomes the new default model on Claude Ma...
蚂蚁百灵发布新一代原生混合推理模型Ling-3.0-Flash
Hi all, So I have been working on document layout analysis for some time now. I have tried the models like Doclayout, Docling, Miner U, marker. I am working with Journals. Overall Docling performs well, but the problem is that it over performs. And mineru u misses some content like the corresponding author on the page-footer. And it is also missing the masthead mark, and the article-type label. In my opinion unlimited OCR performs well in all the tasks, but in general it is failing to recognise...
There are a few reasons why problems from International Mathematical Olympiad function as a good benchmark for LLMs: - The problems are new, not included in the training data of any model - Hard math problems are quite a good proxy for general intelligence capability - These are complex multi-step tasks that can benefit from orchestration / harness engineering Results: Frontier models (sol and fable) were able to get perfect / nearly perfect score regardless of harness. For both sonnet and opus...
Hey everyone, I have been looking into how people source compute for their Inference workloads (and in general). I wanted to understand some specific pain points here. If you've used online services like runpod or vast.ai , your perspective is extremely valuable. Please share your experience in the comments here or by DMing me. I've also made a 2 minute survey form that I would really appreciate if you could fill out. DM me for the link. Thank you!   submitted by   /u/chinmaydag...
I have been running some experiments with smaller open-weight LLMs on multiple-choice questions of Swedish medical licensing exams. On a dataset called MedQA-SWE, GPT-4 scored 84% accuracy in 2024 and o3 scored 88% in 2025 on a smaller, overlapping dataset. With post-training (SFT) on data from earlier years, I got MedGemma-1.5-4B to a passing score of 60% on the final year’s exam. Find the implementation here: But even though they were relea...
Hi all, I recently made an end to end ML platform that eases the pain of going from raw sensor data to a deployed model on an MCU. I wanted to get some feedback from those of you who are interested in the tinyML space on anything I can improve, I intend on keeping it free and open sourced so others can contribute to the development if they would like. One main thing that I tried to add was an auto-labeling tool, as for time series sensor data it is very difficult to manually label data, so my g...
This was my Bachelor's Final Project: implementing YOLO26n inference completely from scratch using ARM64 Assembly Language and C, without relying on existing inference frameworks. The goal was to understand how modern neural network inference engines work at a low level and explore optimization techniques for faster and more efficient edge AI execution on Raspberry Pi 4. The implementation includes: * ARM64 Assembly Language + C inference engine * ARM NEON SIMD optimization * Winograd convo...